Neuraminidase 1 secondary deficiency contributes to CNS pathology in neurological mucopolysaccharidoses via brain protein hypersialylation
Bibliographic record
Abstract
Mucopolysaccharidoses (MPS) are lysosomal storage diseases caused by defects in catabolism of glycosaminoglycans. MPS I, II, III, and VII, which are associated with lysosomal accumulation of heparan sulphate (HS), manifest with neurological deterioration and currently lack effective treatments. We report that neuraminidase 1 (NEU1) activity is drastically reduced in brain tissues of patients with neurological MPS and mouse models but not in neurological lysosomal disorders without HS storage. Accumulated HS disrupts the lysosomal multienzyme complex of NEU1 with cathepsin A, β-galactosidase (GLB1), and glucosamine-6-sulfate sulfatase (GALNS), leading to NEU1 deficiency and partial GLB1 and GALNS deficiencies in cortical tissues and induced pluripotent stem cell-derived (iPSC-derived) cortical neurons of patients with neurological MPS. Increased sialylation of N-linked glycans in brains of patients with MPS and mice implicated insufficient processing of sialylated glycans, except for polysialic acid. Correction of NEU1 activity in MPS IIIC mice by lentiviral (LV) gene transfer ameliorated previously identified hallmarks of the disease, including memory impairment, behavioral traits, and reduced levels of excitatory synapse markers VGLUT1 and PSD95. Overexpression of NEU1 also restored levels of VGLUT1/PSD95-positive puncta in cortical iPSC-derived MPS IIIA neurons. Our results demonstrate that HS-induced secondary NEU1 deficiency and aberrant sialylation of brain glycoproteins constitute what we believe is a novel pathological pathway in the neurological MPS spectrum crucially contributing to CNS pathology.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".